PCSI:一种单篇论文被引频次标准化方法     

伍军红  肖宏  任美亚  冯士雍  丁哲 《图书情报工作》2020,64(23):22-30

[目的/意义] 文章的被引频次一直是量化评价一篇论文学术影响力的重要指标。但在不同学科不同年份发表的论文会因该领域研究论文数、引用滞后等因素呈现较大的差异。因此在对比两篇论文时，难以简单依据被引频次的绝对值来评判论文影响力大小。为此，本文设计了一个新的可计算数学模型，使得每篇论文可以有一个标准化的指标，以便对不同学科不同年份发表的论文的学术影响力进行直接比较。[方法/过程] 通过分析2006、2017两年中国科技类学术期刊各学科论文的被引频次分布规律，采用同学科论文被引频次的分布形态最接近对数正态分布的先设条件，提出一种被引频次标准化指数——Paper Citation Standardized Index （简称PCSI，中文"论文引证标准化指数"）。最后以中国科协优秀科技期刊论文评选结果为例，将它们与论文所属学科全部论文进行实证对比研究。[结果/结论] 结果证明，PCSI对不同年份、不同学科论文的被引频次进行了标准化，反映了被引频次的线性差距，是一种较为理想的单篇论文学术影响力比较评价工具。  相似文献   

The effect of use and access on citations     

Michael J. Kurtz  Guenther Eichhorn  Alberto Accomazzi  Carolyn Grant  Markus Demleitner  Edwin Henneken  Stephen S. Murray 《Information processing & management》2005,41(6):1395-1402

It has been shown (Lawrence, S. (2001). Online or invisible? Nature, 411, 521) that journal articles which have been posted without charge on the internet are more heavily cited than those which have not been. Using data from the NASA Astrophysics Data System (ads.harvard.edu) and from the ArXiv e-print archive at Cornell University (arXiv.org) we examine the causes of this effect.  相似文献   

《情报科学》载文被引分析   总被引：25，自引：5，他引：25  

王惠翔 《情报科学》2002,20(2):148-150

本文以《情报学报》等10种我国图书馆学情报学核心期刊为样本，对《情报科学》载文被10种期刊近三年（1998－2000年）引用情况进行一次调查分析。  相似文献   

2000年化学领域热点研究课题的引文分析   总被引：2，自引：0，他引：2  

赵英莉 《情报科学》2002,20(2):151-154

本文应用文献计量学的方法，对2000年《Chemistry Citation Index》引证的参考文献进行了统计分析，评价出了目前化学领域热点研究课题。  相似文献   

Can Google Scholar and Mendeley help to assess the scholarly impacts of dissertations?     

Kayvan Kousha  Mike Thelwall 《Journal of Informetrics》2019,13(2):467-484

Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013 to 2017 via ProQuest, with a precision of over 95%. Some ProQuest dissertations that were dual indexed with other repositories could not be retrieved with ProQuest-specific searches but could be found with Google Scholar searches of the other repositories. The Google Scholar citation counts were then compared with Mendeley reader counts, a known source of scholarly-like impact data. A fifth of the dissertations had at least one citation recorded in Google Scholar and slightly fewer had at least one Mendeley reader. Based on numerical comparisons, the Mendeley reader counts seem to be more useful for impact assessment purposes for dissertations that are less than two years old, whilst Google Scholar citations are more useful for older dissertations, especially in social sciences, arts and humanities. Google Scholar citation counts may reflect a more scholarly type of impact than that of Mendeley reader counts because dissertations attract a substantial minority of their citations from other dissertations. In summary, the new method now makes it possible for research funders, institutions and others to systematically evaluate the impact of dissertations, although additional Google Scholar queries for other online repositories are needed to ensure comprehensive coverage.  相似文献   

An empirical approach based on quantile regression for estimating citation ageing     

《Journal of Informetrics》2019,13(2):738-750

An aspect of citation behavior, which has received longstanding attention in research, is how articles’ received citations evolve as time passes since their publication (i.e., citation ageing). Citation ageing has been studied mainly by the formulation and fit of mathematical models of diverse complexity. Commonly, these models restrict the shape of citation ageing functions and explicitly take into account factors known to influence citation ageing. An alternative—and less studied—approach is to estimate citation ageing functions using data-driven strategies. However, research following the latter approach has not been consistent in taking into account those factors known to influence citation ageing. In this article, we propose a model-free approach for estimating citation ageing functions which combines quantile regression with a non-parametric specification able to capture citation inflation. The proposed strategy allows taking into account field of research effects, impact level effects, citation inflation effects and skewness in the distribution of cites effects. To test our methodology, we collected a large dataset consisting of more than five million citations to 59,707 research articles spanning 12 dissimilar fields of research and, with this data in hand, tested the proposed strategy.  相似文献   

Predicting citation counts based on deep neural network learning techniques     

《Journal of Informetrics》2019,13(2):485-499

With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics, and bibliometrics establish quantified analysis methods and measurements for evaluating scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to the paper, since this metric is widely utilized in the evaluation of scientific publications and moreover, it serves as the basis for many other metrics such as h-index. In this paper, we propose a novel method for predicting long-term citations of a paper based on the number of its citations in the first few years after publication. In order to train a citation count prediction model, we employed artificial neural network which is a powerful machine learning tool with recently growing applications in many domains including image and text processing. The empirical experiments show that our proposed method outperforms state-of-the-art methods with respect to the prediction accuracy in both yearly and total prediction of the number of citations.  相似文献   

Ranking scientific articles based on bibliometric networks with a weighting scheme     

Yu Zhang  Min Wang  Florian Gottwalt  Morteza Saberi  Elizabeth Chang 《Journal of Informetrics》2019,13(2):616-634

As the volume of scientific articles has grown rapidly over the last decades, evaluating their impact becomes critical for tracing valuable and significant research output. Many studies have proposed various ranking methods to estimate the prestige of academic papers using bibliometric methods. However, the weight of the links in bibliometric networks has been rarely considered for article ranking in existing literature. Such incomplete investigation in bibliometric methods could lead to biased ranking results. Therefore, a novel scientific article ranking algorithm, W-Rank, is introduced in this study proposing a weighting scheme. The scheme assigns weight to the links of citation network and authorship network by measuring citation relevance and author contribution. Combining the weighted bibliometric networks and a propagation algorithm, W-Rank is able to obtain article ranking results that are more reasonable than existing PageRank-based methods. Experiments are conducted on both arXiv hep-th and Microsoft Academic Graph datasets to verify the W-Rank and compare it with three renowned article ranking algorithms. Experimental results prove that the proposed weighting scheme assists the W-Rank in obtaining ranking results of higher accuracy and, in certain perspectives, outperforming the other algorithms.  相似文献   

The distinction machine: Physics journals from the perspective of the Kolmogorov–Smirnov statistic     

《Journal of Informetrics》2019,13(4):100982

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法制探索与明清长篇小说的主题表现     

韩春萌  崔玉霞 《广东教育学院学报》2005,25(6):67-72

明清长篇小说中，有不少涉及到法制问题。尽管有的小说不是纯粹的法制小说，但法制探索是其主题表现的一个重要组成部分。在古代法制文学中，有许多重大而深刻的法制主题，如平等主题、警世主题、复仇主题、冤屈主题等，有的作品则集多个法制主题于一身，形成多元建构的特征。深入研究明清长篇小说中的法制问题及其表现艺术，对于探索中国法制文学的发展历程有着重大的意义。  相似文献